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Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation by Kumar, A., Ridha, S., Ganet, T., Vasant, P., Ilyas, S.U.

“…The impact of each input parameter affecting the pressure drop is quantified using the RF algorithm. © 2020 by the authors.…”
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Comparison of algorithm Support Vector Machine and C4.5 for identification of pests and diseases in chili plants by M, Irfan, N, Lukman, A. A, Alfauzi, J, Jumadi

“…In this study comparing the performance classification techniques of Support Vector Machine (SVM) and C4.5 algorithms. The attributes used consist of Leaves, Stems, and Fruits. …”
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Investigation of throughput and packet drop for Hata model on VANET using NCTUns simulation software for open area and suburban area / Rosmawani Samsudin by Samsudin, Rosmawani

“…The investigation was done from 5 to up 20 V ANET nodes. The algorithms considered are Ad-hoc On-demand Distance Vector (AODV) protocol. …”
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Artificial intelligent power prediction for efficient resource management of WCDMA mobile network by Tee Y.K., Tinng S.K., Koh J., David Y.

“…This artificial intelligent call admission control (CAC) was validated using a dynamic WCDMA mobile network simulator. A few comparative results in downlink have shown that our integrated support vector regression assists genetic algorithm (SVRaGA) is capable of predicting next interval power consumption at Node B with low prediction error and improving the quality of service (QoS) by reducing dropped calls. � 2008 IEICE.…”

Hybrid artificial intelligent algorithm for call admission control in WCDMA mobile network by Tee Y.K., Tiong S.K., Johnny K.S.P., Yeoh E.C.

“…The proposed algorithm, support vector regression assists genetic algorithm (SVRaGA) was tested in a dynamic WCDMA mobile network simulator. …”

A new countermeasure to combat the embedding-based attacks on the goldreich-goldwasser-halevi lattice-based cryptosystem by Arif Mandangan, Nazreen Syazwina Nazaruddin, Muhammad Asyraf Asbullah, Hailiza Kamarulhaili, Che Haziqah Che Hussin, Babarinsa Olayiwola

“…Consequently, the simplified CVP can be reduced to a Shortest-Vector Problem (SVP) variant which can be solved by using lattice-reduction algorithms such as the LLL algorithm in a shorter amount of time. …”
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A new countermeasure to combat the embedding-based attacks on the Goldreich-Goldwasser-Halevi lattice-based cryptosystem by Mandangan, Arif, Nazaruddin, Nazreen Syazwina, Asbullah, Muhammad Asyraf, Kamarulhaili, Hailiza, Che Hussin, Che Haziqah, Olayiwola, Babarinsa

“…Consequently, the simplified CVP can be reduced to a Shortest-Vector Problem (SVP) variant which can be solved by using lattice-reduction algorithms such as the LLL algorithm in a shorter amount of time. …”
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AntNet: a robust routing algorithm for data networks by Haseeb, Shariq, Sidek, Khairul Azami, Ismail, Ahmad Faris, Weng Kin, Lai, Yit Mei, Aw

“…The performance matrix used to compare the algorithms is based on average throughput, packet loss, packet drop and end-to-end delay. …”
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An empirical study of pattern leakage impact during data preprocessing on machine learning-based intrusion detection models reliability by Bouke, Mohamed Aly, Abdullah, Azizol

“…Additionally, we find that some algorithms are more sensitive to data leakage than others, as seen by the drop in model accuracy when built without leakage. …”
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Algorithm of the effect of g-jittren on free convection adjacent to a stretching sheet by Shafie, Sharidan

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Machine learning algorithms for early predicting dropout student online learning by Dewi, Meta Amalya, Kurniadi, Felix Indra, Murad, Dina Fitria, Rabiha, Sucianna Ghadati, Awanis, Romli

“…Of the 4 algorithms used, the highest recall value is in Naive Bayes (1), the highest precision is in Logistic Regression with Lasso (1), while the highest accuracy value (0.99) and F1score (0.97) are obtained from the Support Vector Machine which has value equal to Logistic Regression with Lasso. …”
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Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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A study on the application of discrete curvature feature extraction and optimization algorithms to battery health estimation by Goh, Hui Hwang, An, Zhen, Zhang, Dongdong, Dai, Wei, Kurniawan, Tonni Agustiono, Goh, Kai Chen

“…This study employs two optimization algorithms, namely, particle swarm optimization (PSO) and sparrow optimization algorithm (SSA), in conjunction with least squares support vector machine (LSSVM) to compare the model against three conventional models, namely, Gaussian process regression (GPR), convolutional neural networks (CNN), and long short-term memory (LSTM). …”
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A study on the application of discrete curvature feature extraction and optimization algorithms to battery health estimation by Hui Hwang Goh, Hui Hwang Goh, Zhen An, Zhen An, Dongdong Zhang, Dongdong Zhang, Wei Dai, Wei Dai, Tonni Agustiono Kurniawan, Tonni Agustiono Kurniawan, Kai Chen Goh, Kai Chen Goh

“…This study employs two optimization algorithms, namely, particle swarm optimization (PSO) and sparrow optimization algorithm (SSA), in conjunction with least squares support vector machine (LSSVM) to compare the model against three conventional models, namely, Gaussian process regression (GPR), convolutional neural networks (CNN), and long short-term memory (LSTM). …”
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Quality of service performances of three mobile ad hoc network protocols by Adam, Nabilah

“…The protocols included the Dynamic Source Routing (DSR), Ad Hoc On-demand Distance Vector (AODV) and Temporally Ordered Routing Algorithm (TORA) protocol. …”
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Minimization of torque ripple and flux droop using optimal DTC switching and sector rotation strategy by Ahmad Tarusan, Siti Azura

“…A five-level cascaded H-bridge (CHB) inverter was used in the optimal DTC switching strategy because it had many voltage vectors and could be used for a variety of speed operations. …”
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Indoor occupancy detection using machine learning and environmental sensors / Akindele Segun Afolabi ... [et al.] by Afolabi, Akindele Segun, Akinola, Olubunmi Adewale, Odetoye, Oyinlolu Ayomidotun, Adetiba, Emmanuel

“…The resulting data was used to train six different ML-based classifiers. …”
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Predictive modelling of student academic performance using machine learning approaches : a case study in universiti islam pahang sultan ahmad shah by Nurul Habibah, Abdul Rahman

“…With a huge number of students drop out, the higher education institution’s reputation might be dropped. …”
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The enhanced fault-tolerant AODV routing protocol for Wireless Sensor Network by Che-Aron, Zamree, Mohammed Al-Khateeb, Wajdi Fawzi, Anwar, Farhat

“…In this paper, we address the reliability issue by designing an enhanced fault-tolerant mechanism for Ad hoc On-Demand Distance Vector (AODV) routing protocol used in WSN called the ENhancement of FAult Tolerant (ENFAT) ADOV routing protocol. …”
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Computer-assisted pterygium screening system: a review by Abdani, Siti Raihanah, Zulkifley, Mohd Asyraf, Shahrimin, Mohamad Ibrani, Zulkifley, Nuraisyah Hani

“…During the early stage of automated pterygium screening system development, conventional machine learning techniques such as support vector machines and artificial neural networks are the de facto algorithms to detect the presence of pterygium tissues. …”
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